- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Polarization-controlled and single-transverse-mode vertical-cavity surface-emitting lasers with eye-shaped oxide aperture
摘要： We presented a single-transverse-mode and single-polarization vertical-cavity surface-emitting laser (VCSEL) with an eye-shaped oxide aperture, obtained by enhanced anisotropic oxidation of oxide layer. For apertures with dimensions of 2 ' 4.6 and 3 ' 6 μm2, the orthogonal polarization suppression ratio (OPSR) of the VCSEL was 22 and 19 dB, respectively. A single-mode suppression ratio (SMSR) of more than 25 dB at an output power of 0.5 mW was also achieved for the VCSEL with aperture dimension of 2 ' 4.6 μm2. We believe that the proposed method to realize the mode and polarization control of VCSELs has great potential in future applications. ? 2018 The Japan Society of Applied Physics
关键词： anisotropic oxidation,single-transverse-mode,VCSEL,single-polarization,eye-shaped oxide aperture
更新于2025-11-28 14:24:03
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Based on Spectrum Modeling and Optimization
摘要： Bistatic synthetic aperture radar (SAR) is able to break through the limitation of monostatic SAR on forward-looking area imaging with appropriate geometry configurations. Thanks to such an ability, bistatic forward-looking SAR (BFSAR) has extensive potential practical applications. For the focusing problem of conventional side-looking SAR, ω–k algorithm is accepted as the ideal solution. In this paper, the ω–k algorithm will be discussed in BFSAR geometry. As for the bistatic configuration, spatial domain linearization procedure should be carried out to extract a range variable from the point target reference spectrum (PTRS) in the existing ω–k algorithms. With respect to the BFSAR geometry, nevertheless, the linearization procedure reduces the accuracy of PTRS seriously. To cope with such a problem, a novel ω–k algorithm for BFSAR is proposed. In the proposed method, the range variable is modeled as a parameterized polynomial, and the corresponding PTRS with respect to two-dimensional frequencies is established. Then, the parameters are estimated by differential evolution to minimize the PTRS errors for each range coordinate and frequency point. Based on the estimated PTRS, the BFSAR data can be focused well by the proposed ω–k algorithm. Simulation results verify the effectiveness of the proposed method.
关键词： Bistatic forward-looking synthetic aperture radar (BFSAR),differential evolution (DE),ω–k,point target reference spectrum (PTRS)
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Ship Discrimination with Deep Convolutional Neural Networks in Sar Images
摘要： With the advantages of all-time, all-weather, and wide coverage, synthetic aperture radar (SAR) systems are widely used for ship detection to ensure marine surveillance. However, the azimuth ambiguity and buildings exhibit similar scattering mechanisms of ships, which cause false alarms in the detection of ships. To address this problem, self-designed deep convolutional neural networks with the capability to automatically learn discriminative features is applied in this paper. Two datasets, including one dataset reconstructed from IEEEDataPort SARSHIPDATA and the other constructed from 10 scenes of Sentinel-1 SAR images, are used to evaluate our approach. Experimental results reveal that our model achieves more than 95% classification accuracy on both datasets, demonstrating the effectiveness of our approach.
关键词： ship discrimination,Sentinel-1 images,synthetic aperture radar,deep convolutional neural networks
更新于2025-09-23 15:23:52
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Underwater Imaging Based on LF and Polarization
摘要： The underwater image restoration based on polarization information has achieved good results in improving the image quality in scattering media. However, the previous methods are difficult to obtain the true distribution of degree of polarization in the scene. In this paper, we combine synthetic aperture imaging with polarimetric imaging, and propose a method for retrieving radiation of object based on the degree of polarization and intensity of backscattering at the multi-view image. In addition, compared with the previous methods, the proposed method can achieve simultaneous acquisition of 4D light field information and polarization information, effectively increasing the information dimension obtained by single imaging. In order to verify the effectiveness and superiority of the proposed method, we have established a relevant experimental platform and compared with the experimental results of the previous methods, and obtained the expected experimental results.
关键词： synthetic aperture imaging,polarimetric imaging,underwater image restoration
更新于2025-09-23 15:23:52
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Intensity modulation-based spectral polarization measurement method of coded aperture
摘要： This paper presents a spectral polarization measurement method for single-frame imaging. The method is based on intensity-modulated, coded aperture measurement, comprising a spectral polarization intensity modulation and a compressive sensing spectral imaging system. The incident light is modulated by two multistage phase retarders and a polarizer, and the spectrum's Stokes parameters are shifted to different frequency channels. The spectrum of the modulated light is obtained by a spectral imaging system composed of a coded aperture and a dispersive prism. The modulated spectral information is reconstructed using the TwIST algorithm, and the Stokes elements can be demodulated from it. Taking a pixel as an example, numerical simulations of the modulation of incident light intensity modulation, spectral reconstruction, and demodulation of Stokes parameters show that the method can acquire spectral polarization information of sparse images. This process needs only one measurement of the object and is therefore capable of high-speed acquisition.
关键词： Intensity modulation,Stokes parameters,Coded aperture
更新于2025-09-23 15:23:52
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Automatic bathymetry retrieval from SAR images
摘要： Bathymetry, the topography of the sea floor, is in high demand due to the increase in offshore constructions like wind parks. It is also an important dataset for climate change modelling, when sea level rises and changes in circulation currents are to be simulated. The retrieval of accurate bathymetry data is a cost-intensive task usually requiring a survey vessel charting the respective area. However, bathymetry can also be retrieved remotely using data from Earth observation satellites. The main point of this study is the development of a processor that allows the automatic derivation of gridded bathymetry information from spaceborne Synthetic Aperture Radar (SAR) data. Observations of sea state modifications in SAR images are used to derive the bathymetry in shelf areas using the shoaling effect, which causes wavelengths to become shorter when reaching shallower waters. The water depth is derived using the dispersion relation for surface water waves, which requires wavelength and wave period as input parameters. While the wavelength can be directly retrieved from the SAR image, for the peak period additional information and procedures are required, e.g. local measurements or complex SAR data. A method for automatically deriving the wave period for swell waves in SAR images was developed and tested in this paper. It uses depth data from public databases as initial values which are compared to derived depths iterating through possible peak periods along the calculation grid; the peak period resulting in a minimal root-mean-square deviation is then used for bathymetry calculation. The bathymetry derived from a TerraSAR-X acquisition of the Channel Islands is presented; the resulting peak wave period of 11.3 s fits well to nearby in situ measurement data.
关键词： Bathymetry,Remote sensing,Near-real time processing,Synthetic aperture radar
更新于2025-09-23 15:23:52
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Co-polarization channel imbalance phase estimation by corner-reflector-like targets
摘要： Polarimetric calibration is a critical step to suppress the potential system distortion before implementing any applications for polarimetric synthetic aperture radar (PolSAR). Among all the distortion elements, the crosstalk and cross-pol channel imbalance are generally estimated by the use of natural media, and the co-pol channel imbalance is traditionally solved by the use of corner reflectors (CRs). However, the deployment of ground CRs is costly and may even be impossible in some areas. Many bright point targets, such as poles, lamps, and corner points of structures, are commonly found in manmade regions. In particular, if the object orientation is parallel or perpendicular to the radar flight direction, some points will present similar polarimetric responses to trihedral or dihedral CRs. These points, which are referred to here as "CR-like targets", can be treated as a supplement to approximately solve the system distortion elements when CRs are unavailable. In this paper, we propose a novel step-by-step algorithm to determine the CR-like targets and estimate the co-pol channel imbalance phase in uncalibrated PolSAR imagery. Chinese X-band airborne and C-band satellite PolSAR data were used to test the proposed method. Compared with the CR-derived co-pol channel imbalance phase, the solution errors of the CR-like targets were 1.305° and 0.03° for the X- and C-band experiments, respectively. The results of the experiments confirm that the solutions of the CR-like targets are very close to those of ground-deployed CRs, and the proposed method can be considered as an effective way to calibrate PolSAR images when sufficient CR-like point targets are detected in manmade regions.
关键词： Corner reflector,Polarimetric synthetic aperture radar,Calibration,Target detection
更新于2025-09-23 15:23:52
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[IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Change Detection in Semantic Level for SAR Images
摘要： Considering that the traditional change detection algorithms only focus on extracting the change area but ignore the change content identification, a novel change detection framework for synthetic aperture radar (SAR) images is proposed. The framework integrates the merits of unsupervised and supervised learning to detect changes in semantic level. First, the residual convolutional auto-encoder (RCAE) is designed to convert SAR image slices to the histogram representation. Then, we calculate the difference vectors and extract the change area by their norms. Finally, we classify the difference vectors of change region and identify the content of change. Experimental results indicate that the proposed method significantly achieves performance improvement over existing algorithms.
关键词： semantic,bag of visual words,synthetic aperture radar,auto-encoder,change detection
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - A Novel Tool for Unsupervised Flood Mapping Using Sentinel-1 Images
摘要： In this paper, we present a novel method for mapping flooded areas exploiting Sentinel-1 ground range detected products. The work introduces two novelties. As first, the input products. In fact, as far we know, no applications using these products has been so far presented in literature. Secondly, a new unsupervised methodology, based on the usage of opportune layers combined in a fuzzy decision system, is presented. Experimental results, obtained both on the single SAR image and on a couple of acquisitions in a change detection framework showed that our method is able to outperform the most popular classification techniques in terms of standard assessment parameters.
关键词： flooding,sentinel-1,classification,fuzzy systems,Synthetic aperture radar
更新于2025-09-23 15:23:52
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Temporal Difference and Density-Based Learning Method Applied for Deforestation Detection Using ALOS-2/PALSAR-2
摘要： Remote sensing has established as key technology for monitoring of environmental degradation such as forest clearing. One of the state-of-the-art microwave EO systems for forest monitoring is Japan’s L-band ALOS-2/PALSAR-2 which provides outstanding means for observing tropical forests due its cloud and canopy penetration capability. However, the complexity of the physical backscattering properties of forests and the associated spatial and temporal variabilities, render straightforward change detection methods based on simple thresholding rather inaccurate with high false alarm rates. In this paper, we develop a framework to alleviate problems caused by forest backscatter variability. We define three essential elements, namely “structures of density”, “speed of change”, and “expansion patterns” which are obtained by differential computing between two repeat-pass PALSAR-2 images. To improve both the detection and assessing of deforestation, a “deforestation behavior pattern” is sought through temporal machine learning mechanism of the three proposed elements. Our results indicate that the use of “structure of density” can introduce a more robust performance for detecting deforestation. Meanwhile, “speed of change” and “expansion pattern” are capable to provide additional information with respect to the drivers of deforestation and the land-use change.
关键词： Density-Based,Temporal Difference Learning,Synthetic Aperture Radar (SAR)
更新于2025-09-23 15:23:52